Antimicrobial stewardship in rural nursing homes: Impact of interprofessional education and clinical decision tool implementation on urinary tract infection treatment in a cluster randomized trial
Bibliographic record
Abstract
OBJECTIVES: To measure the impact of an antimicrobial stewardship initiative on the rate of urine culture testing and antimicrobial prescribing for urinary tract infections (UTIs) between control and intervention sites. Secondary objectives included evaluation of potential harms of the intervention and identifying characteristics of the population prescribed antimicrobials for UTI. DESIGN: Cluster randomized controlled trial. SETTING: Nursing homes in rural Alberta, Canada. PARTICIPANTS: The study included 42 nursing homes ranging from 8 to 112 beds.Methods/interventions:Intervention sites received on-site staff education, physician academic detailing, and integrated clinical decision-making tools. Control sites provided standard care. Data were collected for 6 months prior to and 12 months after the intervention. RESULTS: Resident age (83.0 vs 83.8 years) and sex distribution (female, 62.5% vs 64.5%) were similar between the groups. Statistically significant decreases in the rate of urine culture testing (-2.1 tests per 1,000 resident days [RD]; 95% confidence interval [CI], -2.5 to -1.7; P < .001) and antimicrobial prescribing for UTIs (-0.7 prescriptions per 1,000 RD; 95% CI, -1.0 to -0.4; P < .001) were observed in the intervention group. There was no difference in hospital admissions (0.00 admissions per 1,000 RD; 95% CI, -0.4 to 0.3; P = .76), and the mortality rate decreased by 0.2 per 1,000 RD in the intervention group (95% CI, -0.5 to -0.1; P = .002). Chart reviews indicated that UTI symptoms were charted in 16% of cases and that urine culture testing occurred in 64.5% of cases. CONCLUSION: A multimodal antimicrobial stewardship intervention in rural nursing homes significantly decreased the rate of urine culture testing and antimicrobial prescriptions for UTI, with no increase in hospital admissions or mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".